BLOOD GROUP DETECTION USING FINGERPRINT
Abstract & Details
Research Area
Information Technology
Keywords
Blood group detection
Fingerprint analysis
Machine learning
Convolutional Neural Networks (CNN)
MobileNet
RNN
ResNet
Vision Transformer
Biometric applications
Medical diagnostics.
Abstract
This project presents a novel approach for blood group detection using fingerprint analysis, a non-invasive and efficient method that can enhance current blood typing techniques. The study involves classifying fingerprints into eight distinct blood group categories: A+, A-, AB+, AB-, B+, B-, O+, and O-. We employ a variety of advanced machine learning algorithms to achieve high accuracy in classification. Specifically, we utilize Convolutional Neural Networks (CNN), MobileNet, RNN combined with ResNet, and Vision Transformers to analyze fingerprint patterns and extract meaningful features. Our approach focuses on leveraging the unique characteristics of fingerprint minutiae to correlate with specific blood group characteristics. Through comprehensive experiments, we evaluate the performance of each algorithm, assessing their accuracy, precision, and computational efficiency. The results demonstrate the potential of fingerprint-based blood group detection as a reliable alternative to traditional methods. This innovative technique not only provides quick and accurate results but also contributes to the growing field of biometric applications in medical diagnostics. The findings highlight the feasibility of integrating biometric identification systems with healthcare solutions, paving the way for future research in this domain.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | N ANITHA | Siddharth Institute of Engineering & Technology (SIETK) |
| 2 | NAGIREDDY BHAVITHA | Siddharth Institute of Engineering & Technology (SIETK) |
| 3 | PARLAPALLI VARALAKSHMI | Siddharth Institute of Engineering & Technology (SIETK) |
| 4 | THOKALA MUKESH | Siddharth Institute of Engineering & Technology (SIETK) |
| 5 | KUMMARI YOGESH | Siddharth Institute of Engineering & Technology (SIETK) |
| 6 | A BHARATH KUMAR | Siddharth Institute of Engineering & Technology (SIETK) |
How to Cite
Use the following formats to cite this article in your research.
APA Style
ANITHA, N, BHAVITHA, NAGIREDDY, VARALAKSHMI, PARLAPALLI, MUKESH, THOKALA, YOGESH, KUMMARI, & KUMAR, A BHARATH (2025). BLOOD GROUP DETECTION USING FINGERPRINT. International Journal of Advance Research and Innovative Ideas In Education, 11(2), 1457-1464.
MLA Style
ANITHA, N, et al. "BLOOD GROUP DETECTION USING FINGERPRINT." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, 2025, pp. 1457-1464.
IEEE Style
N ANITHA, NAGIREDDY BHAVITHA, PARLAPALLI VARALAKSHMI, THOKALA MUKESH, KUMMARI YOGESH, and A BHARATH KUMAR, "BLOOD GROUP DETECTION USING FINGERPRINT," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 2, pp. 1457-1464, 2025.
Vancouver Style
ANITHA N, BHAVITHA NAGIREDDY, VARALAKSHMI PARLAPALLI, MUKESH THOKALA, YOGESH KUMMARI, KUMAR A BHARATH. BLOOD GROUP DETECTION USING FINGERPRINT. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(2):1457-1464.
Harvard Style
ANITHA, N, BHAVITHA, NAGIREDDY, VARALAKSHMI, PARLAPALLI, MUKESH, THOKALA, YOGESH, KUMMARI, & KUMAR, A BHARATH (2025) 'BLOOD GROUP DETECTION USING FINGERPRINT', International Journal of Advance Research and Innovative Ideas In Education, 11(2), pp. 1457-1464.
Chicago Style
ANITHA, N, et al. "BLOOD GROUP DETECTION USING FINGERPRINT." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 1457-1464.
Turabian Style
ANITHA, N, et al. "BLOOD GROUP DETECTION USING FINGERPRINT." International Journal of Advance Research and Innovative Ideas In Education 11, no. 2 (2025): 1457-1464.
Related Research
DIGITAL DIVIDE AND EQUITY IN ACCESS TO INTERNET: ITS IMPACT TO LEARNERS’ ACADEMIC ACHIEVEMENT
PDF Unavailable
A PHENOMENOLOGICAL STUDY ON THE CHALLENGES, AND COPING STRATEGIES OF SCHOOL HEADS IN USING TECHNOLOGY
PDF Unavailable
INFLUENCE OF TEACHER PERSONAL COMPETENCE AND SCHOOL LEADERSHIP ON STUDENT ACHIEVEMENT IN MEDIA AND INFORMATION LITERACY
PDF Unavailable
A Comprehensive Review of Blockchain in Automotive Data Tracking
PDF Unavailable
IoT-Based Elderly Emergency Health Monitoring System integrated with a Smart Ambulance mechanism
PDF Unavailable
Decentralized Voting System Using Ethereum Blockchain
PDF Unavailable